Client - CyborgDB Docs

Client is the main class exposed by CyborgDB. It exposes the functionality necessary to create, load, list and delete indexes. Operations within encrypted indexes (such as upsert and query) are contained within the EncryptedIndex class returned by create_index and load_index.

Constructor

Client(index_location: DBConfig,
       config_location: DBConfig,
       items_location: DBConfig,
       cpu_threads: int = 0,
       gpu_accelerate: bool = False)

Initializes a new CyborgDB Client instance.

Parameters

Parameter	Type	Default	Description
`index_location`	`DBConfig`	-	Configuration for index storage location. Use a dictionary with keys `location`, `table_name`, and `connection_string`.
`config_location`	`DBConfig`	-	Configuration for index metadata storage. Uses the same dictionary structure as `index_location`.
`items_location`	`DBConfig`	`NONE`	(Optional) Configuration for encrypted item storage. Uses the same dictionary structure as `index_location`.
`cpu_threads`	`int`	`0`	(Optional) Number of CPU threads to use for computations (defaults to `0` = all cores).
`gpu_accelerate`	`bool`	`False`	(Optional) Indicates whether to use GPU acceleration (defaults to `False`).

Exceptions

ValueError

Throws if the cpu_threads parameter is less than 0.
Throws if any DBConfig is invalid.
Throws if the GPU is not available when gpu_accelerate is True.

RuntimeError

Throws if the backing store is not available.
Throws if the Client could not be initialized.

Example Usage

import cyborgdb_core as cyborgdb

index_location = cyborgdb.DBConfig(location='redis', connection_string="redis://localhost")
config_location = cyborgdb.DBConfig(location='redis', connection_string="redis://localhost")
items_location = cyborgdb.DBConfig(location='postgres', table_name="items", connection_string="host=localhost dbname=postgres")

# Construct the Client object
client = cyborgdb.Client(index_location=index_location,
                    config_location=config_location,
                    items_location=items_location,
                    cpu_threads=4,
                    gpu_accelerate=True)

# Proceed with further operations

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